Diagnosing and Repairing Citation Failures in Generative Engine Optimization
Generative Engine Optimization (GEO) aims to improve content visibility in AI-generated responses. However, existing methods measure contribution-how much a document influences a response-rather than citation, the mechanism that actually drives traffic back to creators. Also, these methods apply generic rewriting rules uniformly, failing to diagnose why individual document are not cited. This paper introduces a diagnostic approach to GEO that asks why a document fails to be cited and intervenes accordingly. We develop a unified framework comprising: (1) the first taxonomy of citation failure modes spanning different stages of a citation pipeline; (2) AgentGEO, an agentic system that diagn...
| Authors | Zhihua Tian, Yuhan Chen, Yao Tang et al. |
|---|---|
| Primary category | cs.IR |
| Published | 10 March 2026 |
| Last updated at source | 10 March 2026 |
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